Analysis of the gut microbiome in dogs and cats

Abstract The gut microbiome is an important immune and metabolic organ. Intestinal bacteria produce various metabolites that influence the health of the intestine and other organ systems, including kidney, brain, and heart. Changes in the microbiome in diseased states are termed dysbiosis. The concept of dysbiosis is constantly evolving and includes changes in microbiome diversity and/or structure and functional changes (eg, altered production of bacterial metabolites). Molecular tools are now the standard for microbiome analysis. Sequencing of microbial genes provides information about the bacteria present and their functional potential but lacks standardization and analytical validation of methods and consistency in the reporting of results. This makes it difficult to compare results across studies or for individual clinical patients. The Dysbiosis Index (DI) is a validated quantitative PCR assay for canine fecal samples that measures the abundance of seven important bacterial taxa and summarizes the results as one single number. Reference intervals are established for dogs, and the DI can be used to assess the microbiome in clinical patients over time and in response to therapy (eg, fecal microbiota transplantation). In situ hybridization or immunohistochemistry allows the identification of mucosa‐adherent and intracellular bacteria in animals with intestinal disease, especially granulomatous colitis. Future directions include the measurement of bacterial metabolites in feces or serum as markers for the appropriate function of the microbiome. This article summarizes different approaches to the analysis of gut microbiota and how they might be applicable to research studies and clinical practice in dogs and cats.

| 7 SUCHODOLSKI large intestine, but their contributions to health and disease remain unknown. 3,4 The gut microbiome consists mostly of strict or facultative anaerobic bacteria, especially in the highly populated large intestine. The predominant phyla in dogs and cats are Firmicutes, Fusobacteria, and Bacteroidetes. 5,6 Intestinal bacteria either produce or convert dietary molecules or drugs into bacteria-derived metabolites, and the gut microbiome is considered an important metabolic organ. A balanced gut microbiome exerts a beneficial These microbial effects reach beyond the GI tract. Studies in dogs and cats show that changes in the intestinal microbiome and/ or function are not only present in GI disease, 10,11 but are also associated with disorders in other organ systems such as chronic kidney disease (CKD), 12 heart disease, [13][14][15] neurologic disorders, 16 diabetes mellitus, 17 and obesity. 18 While the exact underlying mechanisms still need to be explored in many of these disorders, some microbial pathways are now well-recognized contributing to health and disease (Table 1), and some of these can be directly assessed using different methods. A better understanding of the gut microbiota and their function will lead to advances in new diagnostic and therapeutic options. This article summarizes different approaches to the analysis of gut microbiota and how they could be applicable to research studies as well as clinical practice.

| A SS E SS MENT OF THE INTE S TINAL MICROB IOME-G ENER AL CONS IDER ATIONS
It is important to emphasize that intestinal bacteria constitute just one part of an intricate relationship that exists between the intestinal epithelial cells, the intestinal mucus layer, the host immune system, and the luminal environment. The composition of the microbiota is influenced to some degree by diet, drugs such as antibiotics and chemotherapeutics, inflammation in the gut, structural changes in the intestine, and others. [19][20][21] Some of these factors have been recently reviewed in detail elsewhere. 22 Therefore, studies should aim to evaluate these mechanisms using complementary approaches (taxonomic and functional) to understand how specific bacteria are modulated by the microenvironment within the gut and under which situations they contribute to health and disease.
There are differences in bacterial populations between the stomach, and the small and large intestine, mostly due to differences in intestinal physiology (difference in oxygen levels, pH, antimicrobial compounds, and intestinal motility). The canine stomach harbors only a few types of bacteria that can survive the acidic environment, predominantly Helicobacter spp. and, to a smaller degree, lactic acidtype bacteria. 23 The small intestine harbors a mix of aerobic and anaerobic bacteria. 24,25 The large intestine is highly populated with mostly anaerobic bacteria. 5,6 Most studies have evaluated the fecal microbiome, as this is the most accessible sample type in clinical settings. Yet, the analysis of fecal samples does not provide complete information about the potential presence of mucosa-adherent or entero-invasive bacteria or the composition and the quantity of the small intestinal microbiota.
There are differences in luminal vs mucosa-adherent bacterial populations, and for some disorders, the assessment of mucosa-adherent bacteria by fluorescence in-situ hybridization (FISH) might be useful. 10,21,26 A recent study used FISH ( Figure 1) to describe bacteria (Helicobacter spp.) deep in the colonic crypts of healthy dogs, and bacteria in these locations could have important immunological properties for health and disease as compared with luminal bacteria. 27 The small intestinal microbiota, even if of normal composition, can contribute to clinical signs when there is an abnormal or increased amount of food or drug substrate in the intestinal lumen. This can be due to feeding diets with poor digestibility, inflammatory diseases that damage the transporters in the epithelial brush border, 28,29 and a lack of digestive enzymes in patients with exocrine pancreatic insufficiency (EPI). 30 Therefore, abnormal microbial conversion of luminal substrates by normal microbiota can be pathologic, not just changes in bacterial populations. While some of the microbiome changes that likely originate in the small intestine can be detected in fecal samples, as reported for dogs receiving omeprazole, 23 37 Changes in the ratios of the SCFAs butyrate, propionate, and acetate influence the expression of virulence factors of Salmonella enterica. 38 Escherichia coli exhibits different growth rates and motility in the ileum vs colon, and this is dependent on differences in the SCFA ratio between these two intestinal sites. 39 Bile acid metabolism is another important bacterial-derived metabolic pathway that, when disrupted, will lead to overgrowth of potential enteropathogens. A disrupted microbiota can lead to a decreased abundance of intestinal bacteria that are able to convert primary to secondary bile acids, which in turn allows the overgrowth of in C hiranonis can be induced by broad-spectrum antibiotics, 42,43 and is often present in chronic inflammatory enteropathies. 11,29,41 Several recent studies have shown that a decrease in the abundance of this bacterium is highly associated with dysbiosis (see below under dysbiosis index). 29,43 Therapeutic modulation with diet or fecal microbiota transplantation can lead to the normalization of C hiranonis abundance, which is associated with normalization of the microbiota. 41,42,44 Another important bacterium is Faecalibacterium prausnitzii, which produces short-chain acid and anti-inflammatory peptides and is often decreased in canine and feline intestinal diseases. 29,43,46

| BAC TERIAL CULTURE
As mentioned above, the majority of intestinal bacteria, especially in the large intestine, are strict anaerobes, and most require special growth media. Some specialized research laboratories are able to cultivate these microbes through a combination of molecular tools to identify bacteria in a sample and then optimize culture conditions for their growth. 47 Traditional bacterial culture, however, as performed in veterinary diagnostic laboratories, vastly underestimates the number of intestinal bacteria because only standard bacterial media and/ or limited anaerobic methods are used. Only a small percentage of bacterial species can be isolated from the feces of clinical patients, and these have been reported by commercial diagnostic laboratories. Unfortunately, because these bacteria are isolated from clinical patients; clinicians often erroneously consider them as pathogens (eg, E coli, C perfringens). 48 In a recent study, three aliquots of fecal samples from healthy dogs and dogs with chronic diarrhea were submitted in a blinded fashion to three veterinary reference laboratories for the evaluation of dysbiosis or the culture of pathogenic bacteria.
The authors ordered a so called "fecal bacterial culture profile". 48 TA B L E 1 Contribution of intestinal bacteria to metabolic pathways that influence health and disease Across all samples, bacterial culture results from all three laboratories did not reveal significant differences in microbiota between healthy dogs and dogs with chronic diarrhea. Interestingly, the laboratories reported dysbiosis more frequently in healthy dogs, and there was no agreement in the reported culture results between the three laboratories. 48 Hemolytic E coli were more frequently isolated from healthy dogs than dogs with diarrhea. This was in contrast with the molecular-based Dysbiosis Index (see below), which was significantly higher, indicating dysbiosis in dogs with chronic diarrhea. 48 These results are not surprising due to the lack of bacterial culture standardization between laboratories, unknown criteria for how a microbiota dysbiosis has been defined by each laboratory, and the fact that most bacteria in the gut are anaerobes and therefore remain undetected. These anaerobic bacteria, which provide various metabolic benefits to the host (Table 1), are typically reduced in acute and chronic intestinal disease. 49,50 It is likely that this reduction in beneficial bacteria and, therefore, microbiome function is clinically more important than an overgrowth of individual facultative cultivable bacterial species (eg, C perfringens). 51 colitis is also recommended, as recent data has shown that these entero-invasive organisms are often resistant to many of the previously recommended antimicrobials (ie, fluoroquinolones). 54

| NE X T-G ENER ATI ON S EQUEN CING
Next-generation sequencing (NGS) includes sequencing of 16S rRNA genes, DNA shotgun sequencing (metagenomics), and metatranscriptomics ( Table 2). The latter approach attempts to assess the gene expression of intestinal microbes but is currently a rarely used method due to the expense and the complexity of analysis. 55 Almost all studies assessing the intestinal microbiota in com-   In sequencing studies, the abundance of bacterial taxa are expressed as relative proportions of the total bacterial community and then statistically compared between treatment groups. There are several factors that will affect the reported relative proportions. The method of DNA extraction (eg, bead-beating vs non-bead-beating, addition of lysozyme, RNAse treatment) will affect the lysis of some bacterial groups more than others. Therefore, some taxa will differ quite significantly in abundance depending on the method used ( Figure 2). 72 The primer selection will affect which variable region of the 16S rRNA gene is targeted, and this has a major impact on which taxa will be preferentially amplified and, therefore, reported in higher proportions. 72 Most studies about gut microbiota target the variable region V4, but it has not been determined which one is preferable for dogs and cats. 73 The choice of the sequencing platform, the chosen bioinformatics pipeline, and the reference database will also affect the reported proportions. 69,74 There are also major differences in how results are reported. Another limitation of current microbiome studies is that authors typically compare the effects of various environmental factors (eg, diet, collection and storage methods, breed influences, geographical location, etc) only to a control group or to its own baseline within the F I G U R E 2 Effect of the DNA extraction method on the abundance of fecal bacteria. Two different DNA extraction methods were compared for canine fecal samples, and the bacterial taxa were measured using identical quantitative PCR (qPCR) assays. 49 Method 1 uses chemical lysis, whereas method 2 49 employs bead beating in addition to chemical lysis. Grey areas indicate the RIs for the targeted bacteria. Differences in methods will affect the measured the abundance in 16S rRNA gene sequencing and qPCR data. It is possible to establish RIs for specific taxa, but assays need to be analytically validated and performed with proper quality control to reproducibly assess the microbiota across studies and in clinical settings study, and in most cases with only a small sample size. Therefore, when changes are observed, it is difficult to extrapolate what the magnitude of observed changes are and how they compare against the wide range of normal microbiota in a large reference population or the targeted disease phenotype since there are no established RIs for bacterial taxa obtained using next-generation sequencing. Also, no true analytical validation of 16S rRNA gene sequencing has been reported; and therefore, no information is available about the reproducibility of sequencing.

| 16S rRNA gene sequencing
In summary, there is no single best approach for 16S rRNA gene

| QUANTITATIVE P CR-THE DYS B I OS IS INDE X
As mentioned above, 16S rRNA gene sequencing reports data as the relative abundance of bacterial taxa within a sample. Therefore, the changes in total bacterial load or abundance of specific taxa between samples are not assessed using an untargeted sequencing approach. 78 For quantitation of total bacteria or individual taxa, qPCR is useful. It is a rapid (less than 24-hour turnaround), affordable (lower equipment and per sample costs), and highly reproducible method to quantify specific taxa, which have been identified as clinically relevant based on previous sequencing studies. 49,79 Quantitative PCR has high reproducibility when the same methods are used (ie, DNA extraction, qPCR primers), and this allows the development of RIs for specific taxa. These reproducible assays can then be used to compare changes in bacterial abundance across studies and assess the magnitude of changes due to an intervention, as the results can be compared to an existing RI (Figure 3). The disadvantage of qPCR is that individual assays must be established for each target of interest.
An example of a qPCR approach is the canine microbiota DI. 49 It measures the abundance of seven bacterial taxa and total bacteria and reports results individually for each bacterial group, as well as combines the abundances in a mathematical algorithm as a DI. These seven bacterial targets have been shown in several studies to be altered in dogs with CE 34,80,81,5333 and antibiotic-induced dysbiosis 42,43,45,82 using 16S rRNA gene sequencing. A DI cut-off above 2 is currently considered dysbiosis, and the higher the DI, the more the microbiota diverges from normal. 29,42 Values between 0 and 2 are equivocal and indicate minor shifts in the microbiome. trol of potential enteropathogens such as C difficile, E coli, and C perfringens. 40,87 Approx. 50%-60% of dogs and 30% of cats with CE have a decreased abundance of C hiranonis and therefore decreased secondary BA. 48,80,88 In humans, the germination of C difficile spores is promoted by a disrupted microbiota and consequently a reduction in secondary and increase in primary bile acids. Similarly, when dysbiosis is present in dogs, for example, due to intestinal inflammation

F I G U R E 3
The effect of different antibiotics on canine fecal microbiota. The data are summarized from three different studies: dogs receiving tylosin (n = 8), 45 metronidazole (n = 16), 43 and amoxicillin-clavulanic acid (n = 6). 84 Dots indicate median values, error bars indicate ranges, grey areas indicate the RIs. All samples were analyzed using the same method (ie, DNA extraction and quantitative PCR assays), 49 and this allows for a better comparison of data across different studies. Furthermore, the data can be compared with existing RIs, allowing conclusions to be drawn as to the magnitude of changes (size effect) of an intervention within the microbiota (Dysbiosis Index [DI]) or on specific bacterial taxa (ie, short-chain fatty acid producing Faecalibacterium spp. and bile acid-converting C hiranonis). These data show that broad-spectrum antibiotics affect the abundance of C hiranonis (below RI), while amoxicillin-clavulanic acid has a limited effect on the DI and C hiranonis or antibiotic use, 42,43,45 this can lead to a lack of C hiranonis, lack of conversion from primary to secondary bile acids, and therefore the proliferation of C difficile. In an unpublished dataset from the author's laboratory, approx. 26% (315/1194) of dogs with chronic diarrhea tested positive for C difficile, and 80% of these lacked the bile acid converting bacterium, C hiranonis. Therefore, the overgrowth of C difficile might reflect the dysbiotic gut environment in CE, which has also been suggested in other studies. 89 91 Therefore, IHC may be a more available option for the identification of intracellular E coli in the future ( Figure 4).

| ME TABOLOMIC S
Metabolomics is an emerging and important area for the assessment of microbiota function and its contribution to health and disease.
Microbial-derived metabolites can be assessed either by targeted and validated assays that measure concentrations of already wellunderstood microbial pathways (eg, SCFA, indoxyl-sulfate, fecal bile acids) or by untargeted assays that measure several hundred different metabolites and are aimed for discovery. Most assays use mass spectrometry platforms. 98 In the discovery phase, the measurement of metabolites should be combined with other phylogenetic Several novel microbial pathways have been characterized in recent years, which affect gut, heart, and kidney function.
The dietary amino acid tryptophan is converted by intestinal bacteria into various indole metabolites. These play an important role in immunoregulation (eg, T-cell response) within the intestine. Indole metabolites act as signaling molecules and can be anti-inflammatory (eg, decrease IL-8 expression), induce mucin gene expression, and strengthen tight junction resistance. 8 Changes in the tryptophanindole pathways are associated with chronic enteropathy in dogs. 99 Dietary supplementation with tryptophan has anti-inflammatory effects in experimental colitis models and is likely a pathway of future investigation in dogs and cats. 100 An increase in the serum concentration of trimethylamine N-oxide (TMAO), a microbial-derived product from the diet (ie, choline and L-carnitine), is associated with atherosclerosis and cardiovascular disease in humans, 101,102 and with chronic heart failure in dogs. 13,103 Similarly, increased TMAO is associated with a poorer prognosis in CKD of people, likely due to its contribution to progressive renal tubulointerstitial fibrosis as shown in animal models. 101 Other gut-derived uremic metabolites, such as branched-chain fatty acids, p-cresol (microbial breakdown of tyrosine and phenylalanine), and indoxyl-sulfate (from tryptophan), have also been associated with CKD in cats. 12,104 Future studies are warranted to understand which bacterial taxa are the main producer of these metabolites and whether dietary modulation (decrease of substrate) or direct microbiota modulation (eg, fiber, probiotics) might be used therapeutically.

| CON CLUS IONS
Much progress has been made over the last several years to better define the intestinal microbiota and their metabolic and immunoregulatory contributions to health and disease. Various complementary tools that assess the microbiota and metabolic pathways are available. In understanding their limitations as well as advantages, specific approaches can be applied to pathway discovery or defined research studies. Initial assays and RIs have been established for specific clinical applications (eg, dysbiosis index, FISH for E coli). As for other organ systems, it is very likely that with time more metabolic pathways and bacterial taxa will be identified as additional microbial biomarkers.

D I SCLOS U R E
The author is an employee of the Gastrointestinal Laboratory at Texas A&M University that offers microbiome and gastrointestinal function testing on a fee-for-service basis.